2021
Scope and Social Determinants of Food Insecurity Among Adults With Atherosclerotic Cardiovascular Disease in the United States
Mahajan S, Grandhi GR, Valero‐Elizondo J, Mszar R, Khera R, Acquah I, Yahya T, Virani SS, Blankstein R, Blaha MJ, Cainzos‐Achirica M, Nasir K. Scope and Social Determinants of Food Insecurity Among Adults With Atherosclerotic Cardiovascular Disease in the United States. Journal Of The American Heart Association 2021, 10: e020028. PMID: 34387089, PMCID: PMC8475063, DOI: 10.1161/jaha.120.020028.Peer-Reviewed Original ResearchConceptsHigh-risk characteristicsUS adultsNational Health Interview Survey dataHealth Interview Survey dataAtherosclerotic cardiovascular diseaseCoronary heart diseaseSelf-reported diagnosisNon-Hispanic blacksInterview Survey dataFood Security Survey ModuleCardiovascular disease resultsLow family incomeAdult Food Security Survey ModuleFood insecurityHeart diseaseASCVDCardiovascular diseasePocket healthcare expenditureHigher oddsSociodemographic determinantsDisease resultsStudy participantsSocial determinantsHealthcare expendituresSociodemographic subgroupsSARS-CoV-2 Infection Hospitalization Rate and Infection Fatality Rate Among the Non-Congregate Population in Connecticut
Mahajan S, Caraballo C, Li SX, Dong Y, Chen L, Huston SK, Srinivasan R, Redlich CA, Ko AI, Faust JS, Forman HP, Krumholz HM. SARS-CoV-2 Infection Hospitalization Rate and Infection Fatality Rate Among the Non-Congregate Population in Connecticut. The American Journal Of Medicine 2021, 134: 812-816.e2. PMID: 33617808, PMCID: PMC7895685, DOI: 10.1016/j.amjmed.2021.01.020.Peer-Reviewed Original ResearchConceptsInfection hospitalization rateInfection fatality rateHospitalization ratesFatality rateSeroprevalence estimatesSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodiesSARS-CoV-2 antibodiesConnecticut Hospital AssociationNon-Hispanic black peopleProportion of deathsCoronavirus disease 2019Total infected individualsTotal hospitalizationsAdverse outcomesNon-congregate settingsHigh burdenDisease 2019Prevalence studyMost subgroupsInfected individualsHospitalizationOlder peopleHospital AssociationConnecticut DepartmentDeath
2020
Burden and Consequences of Financial Hardship From Medical Bills Among Nonelderly Adults With Diabetes Mellitus in the United States
Caraballo C, Valero-Elizondo J, Khera R, Mahajan S, Grandhi GR, Virani SS, Mszar R, Krumholz HM, Nasir K. Burden and Consequences of Financial Hardship From Medical Bills Among Nonelderly Adults With Diabetes Mellitus in the United States. Circulation Cardiovascular Quality And Outcomes 2020, 13: e006139. PMID: 32069093, DOI: 10.1161/circoutcomes.119.006139.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAge FactorsBlack or African AmericanComorbidityCost of IllnessCross-Sectional StudiesDiabetes MellitusFemaleFinancing, PersonalFood SupplyHealth Care CostsHealth Care SurveysHealth ExpendituresHealth Services AccessibilityHumansIncomeMaleMedically UninsuredMiddle AgedPatient ComplianceRisk AssessmentRisk FactorsUnited StatesYoung AdultConceptsDiabetes mellitusMedical billsHigher oddsMedical careNational Health Interview Survey dataHealth Interview Survey dataCost-related medication nonadherenceHigher comorbidity burdenCost-related nonadherenceSelf-reported diagnosisNon-Hispanic blacksInterview Survey dataFinancial hardshipMedication nonadherenceMean ageNonmedical needsHigh prevalenceMellitusMultivariate analysisPocket expenditureFood insecurityNonadherenceHigh financial distressPatientsAdults
2019
Development and Validation of a Model for Predicting the Risk of Acute Kidney Injury Associated With Contrast Volume Levels During Percutaneous Coronary Intervention
Huang C, Li SX, Mahajan S, Testani JM, Wilson FP, Mena CI, Masoudi FA, Rumsfeld JS, Spertus JA, Mortazavi BJ, Krumholz HM. Development and Validation of a Model for Predicting the Risk of Acute Kidney Injury Associated With Contrast Volume Levels During Percutaneous Coronary Intervention. JAMA Network Open 2019, 2: e1916021. PMID: 31755952, PMCID: PMC6902830, DOI: 10.1001/jamanetworkopen.2019.16021.Peer-Reviewed Original ResearchConceptsCreatinine level increaseAcute kidney injuryPercutaneous coronary interventionContrast volumeAKI riskKidney injuryCoronary interventionBaseline riskCardiology National Cardiovascular Data Registry's CathPCI RegistryNational Cardiovascular Data Registry CathPCI RegistryRisk of AKIAcute Kidney Injury AssociatedDifferent baseline risksPCI safetyCathPCI RegistryInjury AssociatedMean ageDerivation setPreprocedural riskMAIN OUTCOMEAmerican CollegePrognostic studiesUS hospitalsCalibration slopeValidation set
2018
Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study
Huang C, Murugiah K, Mahajan S, Li SX, Dhruva SS, Haimovich JS, Wang Y, Schulz WL, Testani JM, Wilson FP, Mena CI, Masoudi FA, Rumsfeld JS, Spertus JA, Mortazavi BJ, Krumholz HM. Enhancing the prediction of acute kidney injury risk after percutaneous coronary intervention using machine learning techniques: A retrospective cohort study. PLOS Medicine 2018, 15: e1002703. PMID: 30481186, PMCID: PMC6258473, DOI: 10.1371/journal.pmed.1002703.Peer-Reviewed Original ResearchMeSH KeywordsAcute Kidney InjuryAgedClinical Decision-MakingData MiningDecision Support TechniquesFemaleHumansMachine LearningMaleMiddle AgedPercutaneous Coronary InterventionProtective FactorsRegistriesReproducibility of ResultsRetrospective StudiesRisk AssessmentRisk FactorsTime FactorsTreatment OutcomeConceptsPercutaneous coronary interventionNational Cardiovascular Data RegistryRisk prediction modelAKI eventsAKI riskCoronary interventionAKI modelMean ageCardiology-National Cardiovascular Data RegistryAcute kidney injury riskAKI risk predictionRetrospective cohort studyIdentification of patientsCandidate variablesAvailable candidate variablesCohort studyPCI proceduresPoint of careBrier scoreAmerican CollegeData registryPatientsCalibration slopeInjury riskSame cohort